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Record W4393904411 · doi:10.1080/08351813.2024.2305045

Communication in Telehealth: A State-of-the-Art Literature Review of Conversation-Analytic Research

2024· article· en· W4393904411 on OpenAlexaff
Lucas M. Seuren, Sakari Ilomäki, Evi Dalmaijer, S. E. Shaw, Wyke Stommel

Bibliographic record

VenueResearch on Language and Social Interaction · 2024
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsTrillium Health Centre
FundersNIHR School for Primary Care ResearchStrategic Research CouncilDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsTelehealthConversationContext (archaeology)Conversation analysisField (mathematics)PsychologyVideoconferencingTelemedicineComputer scienceMultimediaHealth careCommunicationHistoryPolitical science

Abstract

fetched live from OpenAlex

We provide a state-of-the-art review of research on conversation analysis and telehealth. We conducted a systematic review of the literature, focusing on studies that investigate how technology is procedurally consequential for the interaction. We discerned three key topics: the interactional organization, the therapeutic relationship, and the clinical activities of the encounter. The literature on telehealth is highly heterogeneous, with significant differences between text-based care (e.g., via chat or e-mail) and audio(visual) care (e.g., via telephone or video). We discuss the extent to which remote care can be regarded as a demarcated field for study or whether the medium is merely part of the "context," particularly when investigating hybrid and polymedia forms of care involving multiple technological media.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.100
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.100
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0220.024
Science and technology studies0.0020.004
Scholarly communication0.0080.010
Open science0.0030.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.131
GPT teacher head0.549
Teacher spread0.419 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2024
Admission routes1
Has abstractyes

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